Prediction Model on the Relationship of Undergraduate Grades and Licensure Examination Performance of BS Agriculture and Biosystems Engineering
DOI:
https://doi.org/10.65141/ject.v1i1.n2Keywords:
attribute evaluator, classifier, data mining, prediction model, ranker attribute, WEKAAbstract
This study employed WEKA software and data mining techniques in order to identify the critical grade subject(s) needed for passing the licensure examination for BS Agricultural and Biosystems Engineering Licensure exam. This study's proponents examined the ABE licensure exam grades of 84 BSABE graduate students between September 2015 and October 2019, in order to ascertain if higher scores on undergraduate exams correlate with passing the examination. Researchers also created a dataset covering all academic subjects within the BSABE Program, such as Engineering Mathematics, Science Subjects, Major Subjects, General Subjects and Competency Appraisal subjects.Their results suggested that undergraduate students who scored highly on these subjects during their undergraduate studies stood a better chance at passing ABE licensing examination.
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